Evidence map›Paper›PMID 32872296›Full record

ArticleInternational journal of environmental research and public health2020

Comparative Evaluation of Heavy Metal Concentrations in Residents of Abandoned Metal Mines.

Jeong-Wook Seo, Young-Seoub Hong

Open access · goldAbstract readComparative Study
In one paragraph

Article in International journal of environmental research and public health, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.5field-weighted citation impact, top 36% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 8 citations in OpenAlex.

  1. Article
  2. Pollution Risk Prediction for Cadmium in Soil from an Abandoned Mine Based on Random Forest Model.International journal of environmental research and public health · 2023
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors at 1 institution in 1 country.

Jeong-Wook SeoEnvironmental Health Center, Dong-A University, Busan 49201, Korea.ORCID 0000-0002-1909-6714
Young-Seoub HongEnvironmental Health Center, Dong-A University, Busan 49201, Korea.
Dong-A University · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study compares the heavy metal exposure levels of the population of abandoned metal mines, with high risks of environmental pollution and health effects. We used data from a two-stage abandoned metal mines survey (AMS, n = 4467). The Korea National Health and Nutrition Examination Survey (KNHANES) and the Korea National Environmental Health Survey (KNEHS) were used as general population data. Based on the sex and age distribution in the AMS, a simple random sampling was performed, so that the two datasets had the same distribution (KNHANES n = 1815, KNEHS n = 2328). Blood lead concentrations were slightly higher in the AMS than in KNEHS. Blood cadmium concentrations were similar between the two groups. However, the difference in urine cadmium concentrations was pronounced and statistically significant. Moreover, 30.6% of the AMS data for urine cadmium concentration exceeded the 95th percentile of the KNEHS data. The concentration of lead and cadmium in the residents of the abandoned metal mines, i.e., the vulnerable regions, was higher than that in the general population. It is necessary to monitor and manage the vulnerable regions via a more active and extensive survey system.

Indexed as

MiningNutrition SurveysAdultAgedCadmiumEnvironmental ExposureFemaleHumansLeadMaleMetals, HeavyMiddle AgedRepublic of KoreaResidence CharacteristicsCadmiumLeadMetals, Heavyabandoned minecadmiumlead

Identifiers

PMID32872296
PMCPMC7503294
OpenAlexW3082300376

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.